How do you use a data warehouse for your data mining project? Well, you are probably not going to use a data warehouse for your data mining process, while it will be made available of a data mart, which can be considered a partition or a sub-element of a data warehouse. The data marts are set of data that are feed directly from the data warehouse, and related to a specific company area or process. A real-life example is the data mart created to store data related to default events for the purpose of modeling customers probability of default. 

This kind of data mart will collect data from different tables within the data warehouse, properly joining them into new tables that will not communicate with the data warehouse one. We can therefore consider the data mart as an extension of the data warehouse.

Data warehouses are usually classified into three main categories:

• One-level architecture where only a simple database is available and the data warehousing activity is performed by the mean of a virtual component
• Two-level architecture composed of a group of operational databases that are related to different activities, and a proper data warehouse is available
• Three-level architecture with one or more operational database, a reconciled database and a proper data warehouse

Let's now have a closer look to those three different alternatives.